Sentiment-Focused Web Crawling

Vural, A. Gural
Cambazoglu, B. Barla
Karagöz, Pınar
Sentiments and opinions expressed in Web pages towards objects, entities, and products constitute an important portion of the textual content available in the Web. In the last decade, the analysis of such content has gained importance due to its high potential for monetization. Despite the vast interest in sentiment analysis, somewhat surprisingly, the discovery of sentimental or opinionated Web content is mostly ignored. This work aims to fill this gap and addresses the problem of quickly discovering and fetching the sentimental content present in the Web. To this end, we design a sentiment-focused Web crawling framework. In particular, we propose different sentiment-focused Web crawling strategies that prioritize discovered URLs based on their predicted sentiment scores. Through simulations, these strategies are shown to achieve considerable performance improvement over general-purpose Web crawling strategies in discovery of sentimental Web content.


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The advent of Web 2.0 has led to an increase in the amount of sentimental content available in the Web. Such content is often found in social media web sites in the form of product reviews, user comments, testimonials, messages in discussion forums, status updates, and personal blogs as well as in other forms, including opinions in personal pages, news articles, and product descriptions. The analysis of sentimental content has a number of important applications, most important being web search, contextual a...
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Citation Formats
A. G. Vural, B. B. Cambazoglu, and P. Karagöz, “Sentiment-Focused Web Crawling,” ACM TRANSACTIONS ON THE WEB, pp. 0–0, 2014, Accessed: 00, 2020. [Online]. Available: